Elucidating Novel Serum Biomarkers Associated with Pulmonary Tuberculosis Treatment

In an unbiased approach to biomarker discovery, we applied a highly multiplexed proteomic technology (SOMAscan, SomaLogic, Inc, Boulder, CO) to understand changes in proteins from paired serum samples at enrollment and after 8 weeks of TB treatment from 39 patients with pulmonary TB from Kampala, Uganda enrolled in the Center for Disease Control and Prevention’s Tuberculosis Trials Consortium (TBTC) Study 29. This work represents the first large-scale proteomic analysis employing modified DNA aptamers in a study of active tuberculosis (TB). We identified multiple proteins that exhibit significant expression differences during the intensive phase of TB therapy. There was enrichment for proteins in conserved networks of biological processes and function including antimicrobial defense, tissue healing and remodeling, acute phase response, pattern recognition, protease/anti-proteases, complement and coagulation cascade, apoptosis, immunity and inflammation pathways. Members of cytokine pathways such as interferon-gamma, while present, were not as highly represented as might have been predicted. The top proteins that changed between baseline and 8 weeks of therapy were TSP4, TIMP-2, SEPR, MRC-2, Antithrombin III, SAA, CRP, NPS-PLA2, LEAP-1, and LBP. The novel proteins elucidated in this work may provide new insights for understanding TB disease, its treatment and subsequent healing processes that occur in response to effective therapy.     

Serum LncRNAs Profiles Serve as Novel Potential Biomarkers for the Diagnosis of HBV-Positive Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a common malignancy that has a poor prognosis because there is lack of methods for early diagnosis. We aimed to utilize two serum long non-coding RNAs (lncRNAs), uc001ncr and {"type":"entrez-nucleotide","attrs":{"text":"AX800134","term_id":"37653391"}}AX800134, to diagnose hepatitis B virus (HBV)–positive HCC.

Methods

lncRNA microarrays were utilized to measure the differential expression of lncRNAs between tumor tissues and corresponding non-tumor tissues in HBV-positive hapatocellular carcinoma. uc001ncr and {"type":"entrez-nucleotide","attrs":{"text":"AX800134","term_id":"37653391"}}AX800134 were selected as candidate lncRNAs and detected in three independent cohorts containing a total of 684 participants (healthy individuals and chronic HBV patients and HBV-positive HCC patients) who were recruited between March 2011 and December 2012. A logistic regression model was constructed using a training cohort (n = 353) and validated using an independent cohort (n = 181). The area under the receiver operating characteristic curve (AUC) was utilized to evaluate the diagnostic accuracy.

Results

We determined that a panel based on the expression of uc001ncr and {"type":"entrez-nucleotide","attrs":{"text":"AX800134","term_id":"37653391"}}AX800134 accurately diagnosed HBV-positive HCC (AUC values of 0.9494 and 0.9491 for the training and validation cohorts, respectively). The diagnostic performance of the panel remained high in patients with AFP≤400 ng/ml (AUC values of 0.9371 and 0.9527 for the training and validation cohorts, respectively). The panel also diagnosed early HCC (AUC values of 0.9450 and 0.9564 for the training and validation cohorts, respectively).

Conclusion

Our results indicated that the serum expression of uc001ncr and {"type":"entrez-nucleotide","attrs":{"text":"AX800134","term_id":"37653391"}}AX800134 has potential as novel potential biomarker for the diagnosis of HCC, especially in patients with AFP≤400 ng/ml or early-stage disease (BCLC 0+A).     

Circulating B-Lymphocytes as Potential Biomarkers of Tuberculosis Infection Activity

Accurate biomarkers of Mycobacterium tuberculosis infection activity would significantly improve early diagnosis, treatment and management of M. tuberculosis infection. We hypothesised that circulating B-lymphocytes may be useful biomarkers of tuberculosis (TB) infection status in highly TB-endemic settings. Ex-vivo and in-vitro mycobacteria-specific B-cell ELISPOT assays were used to examine the plasmablast (PB) and memory B-cell (MBC) responses in the peripheral blood of adult, healthy, community controls (n = 151) and of active TB patients (n = 48) living in Uganda. Frequencies of mycobacteria-specific PBs were markedly higher in active TB patients compared to healthy controls, and, conversely, MBCs were markedly higher in the healthy controls compared to active TB patients. In addition, the community controls with evidence of latent TB infection had higher peripheral blood PB and MBC responses than those without evidence of TB infection. These data demonstrate that peripheral blood B-cell responses are differentially modulated during latent and active M. tuberculosis infection, and suggest that the PB to MBC ratio may be a useful biomarker of TB infection activity.     

Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma

Objective

To investigate discriminating protein patterns and serum biomarkers between clear cell renal cell carcinoma (ccRCC) patients and healthy controls, as well as between paired pre- and post-operative ccRCC patients.

Methods

We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to identify patients with ccRCC. A total of 162 serum samples were analyzed in this study, among which there were 58 serum samples from ccRCC patients, 40 from additional paired pre- and post-operative ccRCC patients (n = 20), and 64 from healthy volunteers as healthy controls. ClinProTools software identified several distinct markers between ccRCC patients and healthy controls, as well as between pre- and post-operative patients.

Results

Patients with ccRCC could be identified with a mean sensitivity of 88.38% and a mean specificity of 91.67%. Of 67 m/z peaks that differed among the ccRCC, healthy controls, pre- and post-operative ccRCC patients, 24 were significantly different (P<0.05). Three candidate peaks, which were upregulated in ccRCC group and showed a tendency to return to healthy control values after surgery, were identified as peptide regions of RNA-binding protein 6 (RBP6), tubulin beta chain (TUBB), and zinc finger protein 3 (ZFP3) with the m/z values of 1466.98, 1618.22, and 5905.23, respectively.

Conclusion

MB-MALDI-TOF-MS method could generate serum peptidome profiles of ccRCC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.     

Serum MicroRNAs as Potential Biomarkers for Early Diagnosis of Hepatitis C Virus-Related Hepatocellular Carcinoma in Egyptian Patients

Circulating microRNAs are deregulated in liver fibrosis and hepatocellular carcinoma (HCC) and are candidate biomarkers. This study investigated the potential of serum microRNAs; miR-19a, miR-296, miR-130a, miR-195, miR-192, miR-34a, and miR-146a as early diagnostic biomarkers for hepatitis C virus (HCV)-related HCC. As how these microRNAs change during liver fibrosis progression is not clear, we explored their serum levels during fibrosis progression in HCV-associated chronic liver disease (CLD) and if they could serve as non-invasive biomarkers for fibrosis progression to HCC. 112 Egyptian HCV-HCC patients, 125 non-malignant HCV-CLD patients, and 42 healthy controls were included. CLD patients were subdivided according to Metavir fibrosis-scoring. Serum microRNAs were measured by qRT-PCR custom array. Serum microRNAs were deregulated in HCC versus controls, and except miR-130a, they were differentially expressed between HCC and CLD or late fibrosis (F3-F4) subgroup. Serum microRNAs were not significantly different between individual fibrosis-stages or between F1-F2 (early/moderate fibrosis) and F3-F4. Only miR-19a was significantly downregulated from liver fibrosis (F1-F3) to cirrhosis (F4) to HCC. Individual microRNAs discriminated HCC from controls, and except miR-130a, they distinguished HCC from CLD or F3-F4 patients by receiver-operating-characteristic analysis. Multivariate logistic analysis revealed a panel of four microRNAs (miR-19a, miR-195, miR-192, and miR-146a) with high diagnostic accuracy for HCC (AUC = 0.946). The microRNA panel also discriminated HCC from controls (AUC = 0.949), CLD (AUC = 0.945), and F3-F4 (AUC = 0.955). Studied microRNAs were positively correlated in HCC group. miR-19a and miR-34a were correlated with portal vein thrombosis and HCC staging scores, respectively. In conclusion, studied microRNAs, but not miR-130a, could serve as potential early biomarkers for HCC in high-risk groups, with miR-19a as a biomarker for liver fibrosis progression to cirrhosis to HCC. We identified a panel of four serum microRNAs with high accuracy in HCC diagnosis. Additional studies are required to confirm this panel and test its prognostic significance.     

Serum Circulating microRNA Profiling for Identification of Potential Type 2 Diabetes and Obesity Biomarkers

Background and Aim

MicroRNAs are small non-coding RNAs that play important regulatory roles in a variety of biological processes, including complex metabolic processes, such as energy and lipid metabolism, which have been studied in the context of diabetes and obesity. Some particular microRNAs have recently been demonstrated to abundantly and stably exist in serum and to be potentially disease-specific. The aim of this profiling study was to characterize the expression of miRNA in serum samples of obese, nonobese diabetic and obese diabetic individuals to determine whether miRNA expression was deregulated in these serum samples and to identify whether any observed deregulation was specific to either obesity or diabetes or obesity with diabetes.

Patients and Methods

Thirteen patients with type 2 diabetes, 20 obese patients, 16 obese patients with type 2 diabetes and 20 healthy controls were selected for this study. MiRNA PCR panels were employed to screen serum levels of 739 miRNAs in pooled samples from these four groups. We compared the levels of circulating miRNAs between serum pools of each group. Individual validation of the twelve microRNAs selected as promising biomarkers was carried out using RT-qPCR.

Results

Three serum microRNAs, miR-138, miR-15b and miR-376a, were found to have potential as predictive biomarkers in obesity. Use of miR-138 or miR-376a provides a powerful predictive tool for distinguishing obese patients from normal healthy controls, diabetic patients, and obese diabetic patients. In addition, the combination of miR-503 and miR-138 can distinguish diabetic from obese diabetic patients.

Conclusion

This study is the first to show a panel of serum miRNAs for obesity, and compare them with miRNAs identified in serum for diabetes and obesity with diabetes. Our results support the use of some miRNAs extracted from serum samples as potential predictive tools for obesity and type 2 diabetes.     

Discovery of Novel Serum Biomarkers for Prenatal Down Syndrome Screening by Integrative Data Mining

Background

To facilitate the experimental search for novel maternal serum biomarkers in prenatal Down Syndrome screening, we aimed to create a set of candidate biomarkers using a data mining approach.

Methodology/Principal Findings

Because current screening markers are derived from either fetal liver or placental trophoblasts, we reasoned that new biomarkers can primarily be found to be derived from these two tissues. By applying a three-stage filtering strategy on publicly available data from different sources, we identified 49 potential blood-detectable protein biomarkers. Our set contains three biomarkers that are currently widely used in either first- or second-trimester screening (AFP, PAPP-A and fβ-hCG), as well as ten other proteins that are or have been examined as prenatal serum markers. This supports the effectiveness of our strategy and indicates the set contains other markers potentially applicable for screening.

Conclusions/Significance

We anticipate the set will help support further experimental studies for the identification of new Down Syndrome screening markers in maternal blood.     

Identification of Serum Biomarkers for Gastric Cancer Diagnosis Using a Human Proteome Microarray

We aimed to globally discover serum biomarkers for diagnosis of gastric cancer (GC). GC serum autoantibodies were discovered and validated using serum samples from independent patient cohorts encompassing 1,401 participants divided into three groups, i.e. healthy, GC patients, and GC-related disease group. To discover biomarkers for GC, the human proteome microarray was first applied to screen specific autoantibodies in a total of 87 serum samples from GC patients and healthy controls. Potential biomarkers were identified via a statistical analysis protocol. Targeted protein microarrays with only the potential biomarkers were constructed and used to validate the candidate biomarkers using 914 samples. To provide further validation, the abundance of autoantibodies specific to the biomarker candidates was analyzed using enzyme-linked immunosorbent assays. Receiver operating characteristic curves were generated to evaluate the diagnostic accuracy of the serum biomarkers. Finally, the efficacy of prognosis efficacy of the final four biomarkers was evaluated by analyzing the clinical records. The final panel of biomarkers consisting of COPS2, CTSF, NT5E, and TERF1 provides high diagnostic power, with 95% sensitivity and 92% specificity to differentiate GC patients from healthy individuals. Prognosis analysis showed that the panel could also serve as independent predictors of the overall GC patient survival. The panel of four serum biomarkers (COPS2, CTSF, NT5E, and TERF1) could serve as a noninvasive diagnostic index for GC, and the combination of them could potentially be used as a predictor of the overall GC survival rate.Gastric cancer (GC)¹ is the second leading cause of cancer-related deaths. A total of 952,000 new GC cases (6.8% of the total of the new cancer case) and 723,000 deaths (8.8% of the total new cancer case) occurred in 2012 (1). The highest mortality rates have been reported in East Asia, including China, Japan, and Korea (2–4), and ∼60% of new GC cases and deaths worldwide occur in this region. As GC has a 5-year survival rate of less than 15%, accurate diagnosis and prognostic assessment of patients are essential for optimizing therapeutic strategies, predicting the outcome of treatment, extending the survival period of patients, and potentially healing to reduce cancer mortality (5).A variety of serum antigen biomarkers has been used for GC diagnosis and prognosis, e.g. carcinoembryonic antigen, carbohydrate antibody 19-9 (CA19-9), carbohydrate antibody 72-4 (CA72-4), and carbohydrate antibody 50 (CA50); the protein levels of these antigens in serum are usually used as signatures indicating cancer risk. However, generally, these serum antigen biomarkers lack sufficient sensitivity and specificity (6–8).Autoantibodies against proteins that result from abnormal gene expression and gene mutation in patients with various tumors represent another type of serum biomarker (9–12). The corresponding antigens of the autoantibodies are usually recognized as tumor-specific antigens or tumor-associated antigens (13–16). There is particular interest in these autoantibodies due to the potential diagnostic and prognostic applications of the autoantibodies and their corresponding antigens. Indeed, there is a need to identify novel autoantibody-based biomarkers to improve the sensitivity and specificity for the diagnosis of GC.In this study, we used a human proteome microarray containing 16,368 proteins to discover and independently validate serum autoantibodies with potential for diagnosis and prognosis of GC in a set of 1,401 serum samples. The samples were from 537 GC patients, 550 healthy controls, and 314 individuals of GC-related diseases. Four autoantigen serum biomarkers, COP9 constitutive photomorphogenic homolog subunit 2 (COPS2), CTSF, ecto-5′-nucleotidase (NT5E), and telomeric repeat binding factor 1 (TERF1), were identified with a combined diagnostic sensitivity of 95% and specificity of 92%. Furthermore, our data suggested COPS2, CTSF, NT5E, and TERF1 could also serve as potential predictors for prognostic assessment.     

Identification of Novel Biomarkers for Behcet Disease Diagnosis Using Human Proteome Microarray Approach

Behcet disease (BD) is a chronic systemic vasculitis and considered as an autoimmune disease. Although rare, BD can be fatal due to ruptured vascular aneurysms or severe neurological complications. To date, no known biomarker has been reported for this disease, making it difficult to diagnosis in the clinics. To undertake this challenge, we employed the HuProt arrays, each comprised of ∼20,000 unique human proteins, to identify BD-specific autoantibodies using a Two-Phase strategy established previously. In Phase I, we profiled the autoimmunity on the HuProt arrays with 75 serum samples collected from 40 BD patients, 15 diagnosed autoimmune patients who suffer from Takayasu arteritis (TA; n = 5)), ANCA associated vasculitis (AAV; n = 5), and Sjogren's syndrome (SS; n = 5), and 20 healthy subjects, and identified 20 candidate autoantigens that were significantly associated with BD. To validate these candidates, in Phase II we constructed a focused array with these 20 candidate BD-associated antigens, and use it to profile a much larger cohort, comprised of serum samples collected from 130 BD patients, 103 autoimmune patients (i.e. 40TA, 40 AAV and 23 SS), and 110 healthy controls. This allowed us to validate CTDP1 (RNA polymerase II subunit A C-terminal domain phosphatase)as a BD-specific autoantigen. The association of anti-CTDP1 with BD patients was further validated using the traditional Western blotting analysis. In conclusion, anti-CTDP1 antibody serves a novel autoantibody for Behcet disease and is expected to help more accurate clinical diagnosis.     

Identification of Circulating MicroRNAs as Potential Biomarkers for Detecting Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is the most common acute leukemia in adults. The disease is characterized by various cytogenetic and molecular abnormalities with distinct prognoses and gene expression profiles. Emerging evidence has suggested that circulating microRNAs (miRNAs) could serve as noninvasive biomarkers for cancer detection; however, little is known about circulating miRNA profiles in AML patients. In this study, a genome-wide serum miRNA expression analysis was performed using Solexa sequencing for initial screen, followed by validation with real-time PCR assays. The analysis was conducted on training and verification sets of serum samples from 140 newly diagnosed AML patients and 135 normal adult donors. After a two-phase selection and validation process, 6 miRNAs, miR-10a-5p, miR-93-5p, miR-129-5p, miR-155-5p, miR-181b-5p and miR-320d, were found to have significantly different expression levels in AML compared with control serum samples. Furthermore, unsupervised clustering analysis revealed the remarkable ability of the 6-miRNA profile to differentiate between AML patients and normal controls. The areas under the ROC curve for the selected miRNAs ranged from 0.8129 to 0.9531. More importantly, miR-181b-5p levels in serum were significantly associated with overall survival. These data demonstrated that the expression patterns of circulating miRNAs were systematically altered in AML and miR-181b-5p may serve as a predictor for overall survival in AML patients.